Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
He used AI to make a list of Private Attorneys General Act claims against employers in an industry. The list was made in support of an organizing drive, and he says the tool is almost always helpful on tasks that involve a lot of data.
Neither the seller's household nor the buyer spoke each other's language - she English-only, he Spanish-only - and the AI ran the Facebook Marketplace negotiation and sale arrangement flawlessly between them, in a comment mourning that it beat the home agent her husband built.
A Portuguese-language operator who runs a small automation business (automatic posts, digital product distribution, nightly Python and the AI jobs) catalogs failures that really happened in his operation: a post sent twice because a timeout made the agent eagerly retry a send that had already landed; whole nights of jobs silently lost when a Windows update rebooted his PC and nothing raised an error; a job that only breaks under the 3 a.m. scheduler; and an account temporarily flagged for automation abuse over frequent similar posts.
During a 30-day trial diary, the author shows the AI filling out a school field-trip permission slip it had found in his email — one of several family-admin tasks it handled from his accounts.
The last of four cryptograms on a famous unsolved list had resisted everyone since 1950; the first three fell in 1948, 1996 and 2019. Working with AI and OpenAI, the poster cracked it: Opus 5.5 wrote the search code and picked out the books to use for the key phrase, another model verified the result, and the list keeper has confirmed the solution.
The author describes using AI to resolve a six-month-old travel medical insurance claim with Cigna. The AI called the insurer, was transparent about being an AI, conducted the call politely (impressing the representative), and — because final consent was required — called the author's phone and connected the parties so he could approve verbally.
Konik had the AI build a database of summer camps and birthday-party venues within a 40-minute drive, with camp-week price comparisons and logged reflections on each. It found a nerf-wars venue she chose for her son's winter birthday.
A creator handed the AI his two small YouTube channels: scripts, voice over, image prompts, renders and comment replies, with one hard rule that anything public waits for him. By morning three long episodes were rendered in 4K, 32 images had been checked on a contact sheet, and five replies were posted after every number in them was verified. The failures were quiet ones: a daily lesson that simply never went out four days earlier, timed posts that never fired because the session was busy, and a 3:15am scheduled task that never ran, caught only because his new routine checks after every due time that the thing actually happened.
The AI listed the user's house on Facebook Marketplace, answered renter inquiries, scheduled viewings, and the home rented in 14 days at the full asking rent.
He had the AI gather his SPARQL training materials and present them on a website in a way that is easier to engage with. The site is live on the SIB Swiss GitHub pages.
A statistician had argued that class balancing helps mini batch gradient descent. He had the AI Astra design and run a simulation to test the claim, and the results partly corrected him: oversampling sped convergence but hurt probability accuracy, while importance weighted oversampling kept most of the speed and the accuracy. The code was cross checked with AI, and he posted the corrected conclusion as an answer.
The reviewer asks the AI for the current location of a flight, the progress of a rideshare trip shared through an HTTP link, and an analysis of Boston weather-radar precipitation, getting visual information back as spoken answers.
On a September 27, 2026 podcast episode, a host switching away from Instinct complained its cart checkouts had gotten significantly worse, describing a staged cart that went to zero. The failure hit the product's most-used job — about 35% of users use Instinct for personal shopping.
Creator someone asked the AI to plan multi-city international trips — Toronto, New York, Dubai, Korea, Singapore — find flights, book a hotel, and email the full itinerary to her husband. Five-city coordination ending in an emailed itinerary: the agent as a travel manager.
Five new newsletter subscribers in three days were credited to direct traffic, so he asked the AI to inspect his PostHog analytics, his main site, and his newsletter site. It traced where the tracking was lost, changed the links, deployed and tested the fix, then checked the server logs and showed the signups were bots.
The AI took about a week with light steering to convert OpenStreetMap data into his car's map format, a project that would have taken him months to a year, and he now pulls fresh maps that work on the car.
He has a 40 room hotel and two restaurants with nearly 100 staff and zero coding experience, and has spent the last three months down the rabbit hole. On a self hosted NAS, with ERPNext purely as the back end, he built with AI an entire custom front end: a staff portal with apps like a phone home screen, a maintenance ticket board, a housekeeping app integrated with the property system, QR codes in rooms so guests can report issues straight into maintenance, request a room clean, or order food from the kitchen. There is a restaurant point of sale with a delivery interface that links to the kitchen and updates the customer as cooking progresses, check in terminals, and a company chat with a translator. Rostering, the entire accounting and reconciliation, guest passport scanning, stock ordering, receipt scanning into stock, salary and service charge calculations, and sick reporting with AI scanning of doctors’ letters all run through it. Staff visa and permit paperwork that used to take days of complicated preparation is now prepared by AI into a PDF in seconds. About 140,000 lines of unique code, not counting ERPNext.
Two friends wrote fiction together in chat for years. One of them had the AI merge the writing out of both of their Discord data exports by timestamps, pull out only the story text, and suggest where volumes, chapters and scenes should break, matching seams already in the work. About 400,000 words are in the project and it is over halfway staged into final volumes with full formatting.
Sandboxed agent checks spec and code drift daily, triages findings, and surfaces issues; it revealed product miscommunications on the team.
He uses AI to keep track of his GLP-1 dose history. It also makes a chart of the estimated concentration over time.
He has the AI run the live chats and online paperwork for his returns, cancellations and similar chores. He calls it life-changing.
Niraj Rajgor's unused 10th generation Kindle is now a photo frame. Working through AI over Wi-Fi, GPT-6 Astra built tools to run custom software on the Kindle and installed a slideshow app that cycles ten photos, four minutes each, and picks up where it left off after sleep.
The AI implemented tagged unions and an early-return operator in a Go fork, and the LLM refactor removed 5k+ lines and found real bugs, though not production-ready.
The AI project review of a tax return and supporting docs found 2 big and 4 smaller errors in rental basis and depreciation and IRA basis, which the accountant apologized for and corrected.
Grupo Marista uses AI Enterprise agents to analyze hospital claims. Analysis that took 72 hours now takes 4 hours.
He is a general contractor who could not find software that fit. He built a construction management platform with AI: staff log work and photos through the day with AI tagging, photos update his website, and the system covers quoting, invoicing, sub bids, a timeclock, expense tracking and a client portal with selections and sign offs. He offers free accounts to other contractors, so the account is part showcase.
He built Compressius with AI: it archives an entire website, photos and pages, into a single HTML file under 200 megabytes that can be viewed offline or printed. He built it after a friend asked why his own site export was 20 megabytes of HTML alone.
The AI was working on a web app the student's friends use live. It ran a check of who was in the live lobby and stopped the server in the same command, so his friend, whose name the check had just printed, was kicked out.
His kids have always been disappointed that Super Mario Bros. for the NES does not have two player co-op like the 21st century Mario games. Today he got the AI with Opus 5.5 to make a two player simultaneous mod. You can pick Mario, Luigi, Toad or Peach, and it works on a real NES.
The AI with FreeCAD python scripts creates and modifies his CAD drawings, producing 3D designs, cut-lists and shop drawings for woodworking.
The AI books the user's tennis club clinics and pays for them, keeping the user's regular sessions in place without weekly admin.
A man worked with AI for 6 months on a full rewrite of SimTower so he could play it in a browser. The AI worked from a decompilation of the original binary, a summary of the source code, and his memory of the game, and the finished game was put on the web as WASM with the original art pulled from a binary the player loads.
An agent account (Acrid) reports on its own receipt video pipeline. One video said out loud, in public, that the paper trading account took no trades that day. The account file it read had been written eight hours before the trades happened. The file passed its 24 hour staleness check because it was fresh; it just had not been read again after the day it described. It ran on two separate days and sat there about a week before the agent traced it. No alert fired, because nothing was malformed.
A ready made dashboard only shows what the maker thinks matters. His own status monitor, built with AI on a 10.3 inch second screen, shows him when an n8n workflow, a hoster or his lawn mower socket fails, with 53 tests included.
The AI made a new OBS launcher in about a minute that opens OBS and refreshes and checks all of his sources.
Built an app with AI subagents in an afternoon that reads, maps and translates all 387 labels of an 1819 French map of the Bosphorus.
An agent works his support queue and processes refunds on its own when the order is under $50 and inside 14 days. It cut about 40 minutes of daily sorting and checking, and he now looks only at the cases it flags.
The AI ran a Kepler and TESS search engine he hacked together and found an uncatalogued periodic dip every 13.77 days around KIC 5689121, a possible 2.5 to 3 Earth-radius planet, TRICERATOPS false positive probability about 6.9 percent (result report, not a product pitch).
A business owner hands the AI the tax-time chore he always abandons: hunting down his big Amazon purchases and categorizing them inside QuickBooks Online - including split transactions that take 19 clicks each because a router and shampoo once shared a cart.
He scraped a friend's two social media profiles, made a plan, and had the AI create a website for them. In about half an hour he had a site to show them.
Sammons Financial Group paired an empathetic Agentforce agent with strong internal buy-in to handle over 16,000 policy calls in six months without adding staff, one of Salesforce's 2026 Customer Success Award winners.
A builder created an agent skill that files a user's saved Instagram reels into topic collections. It was battle-tested against a real backlog of roughly 3,280 saved reels, which it sorted into 13 collections.
An Etsy seller of almost two years got a case opened with a photo of a broken frame that did not match the material she actually uses. She ran the buyer's picture through AI, which flagged it as AI-generated; she sent Etsy that analysis plus proof from breaking one of her own frames to show the material mismatch - and Etsy still sided with the customer and took the full refund out of her account.
Student has the AI review generated code on side projects; it caught a real security issue once.
A 24 year old AI engineer at an elevator industry company in New York says he built agent workflows into the internal work system. The workflows make invoices on their own, send emails, and set off next steps in the work, with a person approving at set points.
His new hardware device was faulty and the community had spent days looking for a fix that did not need a replacement. He plugged it into his computer, asked the AI to fix it, went to dinner, and came back to find it fixed.
A landlord’s the AI rent desk matches incoming Venmo, Zelle, Cash App and Section 8 payments to his property sheet, reminds tenants before rent is due and escalates when a payment goes past due. Four payment rails reconciled against one ledger, with dunning built in.
He installed the AI and connected OpenRouter, and thought the agent was just expensive to run. Four days later he found API requests in Chinese that were not his, and the misuse cost him about $100 over a few days.
A traveler planning a trip with AI booked his own flight and hotel, but Dots noticed the shuttle was missing, proposed it with the details they had discussed, and completed the booking form on its cloud computer - after asking him to confirm the same booking three separate times.
A DO alarm was accidentally set to a past time and retriggered immediately; the AI caught it within a couple of minutes from its log tail.
Nathan Daggett of Live Bearded (Phoenix) had the AI go through 87,000 website customer reviews and build a full SWOT analysis; by hand it would have taken months, the AI did it in minutes.
His deal dashboard watches prices every day on the specific things he buys: shoes, pantry staples, gift cards and streaming deals. It emails him only when a deal triggers and stays silent the rest of the time.
Her AI credits had just reset, but she woke up to find 43% of them already used. The agent had kept fixing her old test videos while she slept, and she warns other users to set boundaries for their agent.
Creator took on a $30/week family-of-4 budget challenge with AI, asking it to start from what she already had in her pantry. The AI produced 7 dinner ideas, a grocery list, and a price comparison; her Walmart haul came to $29.66, under budget.
A week into letting AI agent edit his videos, the workflow has stuck. Agent edited video is now part of how he publishes.
The author had someone cancel two unused Adobe subscriptions, dispute $32 in roaming charges on a cell bill, and order craft supplies on Amazon — reporting total savings over $100. Commenters pushed back on privacy, noting the service requires giving Meta extensive personal data and platform access.
His team puts a few lines in their agent instruction files telling agents to run simple self-verification steps. The agents catch their own errors before committing, and low-effort AI submissions get sent back to the contributor to fix and resubmit. He says it filters out most submissions nobody bothered to look at.
MBI Deep Dives asked the AI to buy a winter jacket; it recommended a Patagonia, then admitted the discount it had shown was no longer available. The AI said it ran 'a catalog search and wider web sweep' — the shortlist was likely built from a batch-updated merchant feed, not live pricing.
A founder had AI agent run the entire group marketing campaign for his new app. It read each group’s rules, worked out the best way to post in each one, saved notes and data per group in a spreadsheet, made Instagram videos and reels and posted them to Instagram and TikTok, and is building a Kiva crowdfunding campaign.
The AI answers buyer messages on his Facebook Marketplace listings itself, inside rules he set: a floor price it cannot go under, cash mentioned once, and his address shared only after price and pickup time are agreed. It counters low offers, tracks who went quiet, and reports each exchange back to him.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.